Probabilistic evaluation of quantile estimators

Abstract

The foundations of the criteria to assess the goodness of quantile estimators for continuous random variables are reviewed and the probabilistic justification for a novel bin-criterion is presented. It is shown that the bin-criterion is a more appropriate measure of goodness of a quantile estimator than those based on minimizing the bias of the quantiles or the parameters of the distribution.